The difference between health and disease frequently depends on whether or not certain biomolecules of an organism are within tightly controlled tolerances. This has led to an active search for quantitative molecular biomarkers to assess states of health and disease, e.g. Slamon et al, Science, 240: 1795-1798 (1988); Sidransky, Nature Reviews Cancer, 2: 210-219 (2002); Pinkel and Albertson, Ann. Rev. Genomics Hum. Genet., 6: 331-354 (2005); Stankiewicz and Lupski, Trends in Genetics, 18: 74-82 (2002); Hanna, Oncology, 61 (suppl 2): 22-30 (2001); Cronin et al, Am. J. Pathol., 164: 35-42 (2004); and the like. Although many techniques are available to measure amounts of biomolecules, they each have trade-offs with respect to sensitivity, selectivity, dynamic range, convenience, robustness, cost, and so on. For nucleic acid measurements, most techniques provide analog readouts, in that measured amounts are correlated with signal intensities, e.g. Pinkel and Albertson, Nature Genetics Supplement, 37: S11-S17 (2005); Lockhart et al, Nature Biotechnology, 14: 1675-1680 (1996). Digital measurements of polynucleotides have been made, where measured amounts are correlated with integral numbers of countable events, e.g. numbers of sequence tags; however, even though such measurements have significant statistical advantages, they are usually more difficult and expensive to implement, e.g. Brenner et al, Nature Biotechnology, 18:630-634 (2000); Velculescu et al, Science, 270: 484-487 (1995); Dressman et al, Proc. Natl. Acad. Sci., 100: 8817-8822 (2003); Audic and Claverie, Genome Research, 7: 986-995 (1997).
In view of the great interest, particularly in the cancer field, of the potential prognostic value of genomic copy number changes, the availability of a cost-effective technique for providing digital measurements of biomolecules would be highly desirable in many areas in the biomedical and biological sciences.